{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [java多线程编程详细入门教程_未完全理解](https://blog.csdn.net/liuyuanq123/article/details/80264583)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 概念\n",
    "线程是jvm调度的最小单元，也叫做轻量级进程，进程是由线程组成，线程拥有私有的程序技术器以及栈，并且能够访问堆中的共享资源。这里提出一个问题，为什么要用多线程？有一下几点，首先，随着cpu核心数的增加，计算机硬件的并行计算能力得到提升，而同一个时刻一个线程只能运行在一个cpu上，那么计算机的资源被浪费了，所以需要使用多线程。其次，也是为了提高系统的响应速度，如果系统只有一个线程可以执行，那么当不同用户有不同的请求时，由于上一个请求没处理完，那么其他的用户必定需要在一个队列中等待，大大降低响应速度，所以需要多线程。这里继续介绍多线程的几种状态：\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "这里可以看到多线程有六种状态，分别是就绪态，运行态，死亡态，阻塞态，等待态，和超时等待态，各种状态之间的切换如上图所示。这里的状态切换是通过synchronized锁下的方法实现，对应的Lock锁下的方法同样可以实现这些切换。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 线程的创建\n",
    "线程的创建有两种方式，第一种是**继承Thread类**，第二种是**实现Runnable接口**。\n",
    "\n",
    "第一种代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T13:45+0000",
     "start_time": "2020-11-09T13:45:31.723Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyThread extends Thread{\n",
    "    int j=20;\n",
    "    public void run(){\n",
    "        for (int i = 0; i < 20; i++) {\n",
    "            try {\n",
    "                Thread.sleep(100);  //休眠1min\n",
    "            } catch (InterruptedException e) {\n",
    "                // TODO Auto-generated catch block\n",
    "                e.printStackTrace();\n",
    "            }\n",
    "            System.out.println(this.getName()+\",i=\"+j--);//getName(): 该方法继承自Thread类\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T13:45+0000",
     "start_time": "2020-11-09T13:45:34.226Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "MyThread mythread = new MyThread();\n",
    "mythread.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "第二种方法："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T13:46+0000",
     "start_time": "2020-11-09T13:46:48.306Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRunnable implements Runnable{\n",
    "    int j=20;\n",
    "    @Override//重写run方法\n",
    "    public void run() {\n",
    "        for (int i = 0; i < 20; i++) {\n",
    "            System.out.println(Thread.currentThread().getName()+\",j=\"+this.j--);\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T13:56+0000",
     "start_time": "2020-11-09T13:56:19.291Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "MyRunnable myRunnable = new MyRunnable();\n",
    "Thread t1 = new Thread(myRunnable);\n",
    "Thread t2 = new Thread(myRunnable);\n",
    "t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这就是两种创建线程的方法，在这两种方法中第二种方法时一般情况下的用法，因为继承只能继承一个类，但是可以实现多个接口，这样拓展性更好。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 线程安全测试\n",
    "线程安全是多线程编程中经常需要考虑的一个问题，*线程安全是指多线程环境下多个线程可能会同时对同一段代码或者共享变量进行执行*，**如果每次运行的结果和单线程下的结果是一致的，那么就是线程安全的，如果每次运行的结果不一致，那么就是线程不安全的**。这里对线程安全做一个测试："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T14:03+0000",
     "start_time": "2020-11-09T14:03:10.261Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRunnable implements Runnable{\n",
    "    static int j=1000;\n",
    "    @Override\n",
    "    public void run() {\n",
    "        for (int i = 0; i < 500; i++) {\n",
    "            System.out.println(j--);\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T14:03+0000",
     "start_time": "2020-11-09T14:03:12.300Z"
    }
   },
   "outputs": [],
   "source": [
    "MyRunnable myRunnable = new MyRunnable();\n",
    "Thread t1 = new Thread(myRunnable);\n",
    "Thread t2 = new Thread(myRunnable);\n",
    "t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，这里同时两个线程同时对共享变量j进行访问，并且减1。\n",
    "\n",
    "并且多次执行程序的结果还不一致，这就是线程不安全的情况，通过加锁可以保证线程安全。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 锁\n",
    "java中有两种锁，一种是**重量级锁synchronized**，*jdk1.6经过锁优化加入了偏向锁和轻量级锁*，另一种是JUC并发包下的Lock锁，synchronized锁也称对象锁，每个对象都有一个对象锁。这里通过加锁的方式实现线程安全：\n",
    "\n",
    "代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T14:01+0000",
     "start_time": "2020-11-09T14:01:48.363Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRunnable implements Runnable{\n",
    "    static int j=1000;\n",
    "    @Override\n",
    "    public synchronized void run() {\n",
    "        for (int i = 0; i < 500; i++) {\n",
    "            System.out.println(j--);\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-09T14:02+0000",
     "start_time": "2020-11-09T14:02:43.531Z"
    }
   },
   "outputs": [],
   "source": [
    "MyRunnable myRunnable = new MyRunnable();\n",
    "Thread t1 = new Thread(myRunnable);\n",
    "Thread t2 = new Thread(myRunnable);\n",
    "t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "main中创建两个线程，测试多次的结果都是一样的：\n",
    "\n",
    "说明实现的线程安全，因为当加锁过后，每次只能有一个线程访问被加锁的代码，这样就不会出现线程安全了。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# sleep\n",
    "sleep是让当前线程睡眠，睡眠一段时间后重新获取到cpu的使用权。\n",
    "\n",
    "代码如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "try {\n",
    "    Thread.sleep(100);\n",
    "} catch (InterruptedException e) {\n",
    "    // TODO Auto-generated catch block\n",
    "    e.printStackTrace();\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里表示线程会睡眠100ms后再次到就绪状态中，**这里为什么sleep是Thread的类方法而不是线程的方法，因为，能调用sleep的线程肯定是运行着的，而其他线程也是未运行的，所以调用其他线程的sleep是没有意义的**。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# wait、notify\n",
    "**wait表示当前线程释放掉锁进入等待状态，所以调用wait和notify的前提是已经获取到对象的锁**，如果没有获取到锁就使用wait那么会出异常信息。而**进入等待状态的线程需要通过notify或者通过中断来唤醒进入到阻塞状态来等待锁的获取**。这里对这种情况进行测试，使用notify唤醒一个等待状态的线程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:44+0000",
     "start_time": "2020-11-10T02:44:54.566Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyThreadd extends Thread{\n",
    "    public MyThreadd(String name) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        super(name);\n",
    "    }\n",
    "    public void run(){\n",
    "        synchronized (this) {\n",
    "            System.out.println(Thread.currentThread().getName()+\" notify a thread\");\n",
    "            notify();\n",
    "        }\n",
    "        while(true);\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:44+0000",
     "start_time": "2020-11-10T02:44:56.526Z"
    }
   },
   "outputs": [],
   "source": [
    "//main\n",
    "MyThreadd t1 = new MyThreadd(\"t1\");\n",
    "synchronized (t1) {\n",
    "    System.out.println(Thread.currentThread().getName()+\" start t1\");\n",
    "    t1.start();\n",
    "    System.out.println(Thread.currentThread().getName()+\" wait\");\n",
    "    t1.wait();\n",
    "    System.out.println(Thread.currentThread().getName()+\" waked up\");\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里可以看到，在main函数中，主线程将创建一个线程t1然后进入t1的锁的同步块中启动线程t1，然后调用wait进入等待状态，这个时候线程t1也进入到同步块中，调用notify后释放掉锁，可以看到主线程后续的东西继续被输出。当有多个线程调用了wait之后如果采用notify只会随机的唤醒其中的一个线程进入阻塞态，而采用notifyall会将所有的线程给唤醒。在线程运行结束后会调用notifyall将所有等待状态的线程唤醒。"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# join\n",
    "join的作用是让父线程等待子线程运行结束后在运行，通过查看源码可以知道：\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "其实也是调用了先获取到子线程的锁然后调用wait方法来实现的，因为当子线程运行结束后会调用notifyall所以主线程会被唤醒并且再次获取到子线程的锁继续运行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:48+0000",
     "start_time": "2020-11-10T02:48:49.566Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRuu extends Thread{\n",
    "    public MyRuu(String name) {\n",
    "        super(name);\n",
    "    }\n",
    "    public void run() {\n",
    "        System.out.println(Thread.currentThread().getName());\n",
    "        //while(true);\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:48+0000",
     "start_time": "2020-11-10T02:48:58.677Z"
    }
   },
   "outputs": [],
   "source": [
    "//main\n",
    "MyRuu myRuu = new MyRuu(\"t1\");\n",
    "System.out.println(Thread.currentThread().getName()+\" start t1\");\n",
    "myRuu.start();\n",
    "System.out.println(Thread.currentThread().getName() +\" join\");\n",
    "myRuu.join();\n",
    "System.out.println(Thread.currentThread().getName() +\" waked up\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，当主线程调用join后子线程开始运行，等子线程运行结束后主线程被唤醒。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# yeild\n",
    "yeild的作用是线程让步，当前线调用yeild方法后线程从运行态进入到就绪态重新进入到CPU资源的竞争中。这里进行测试："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:50+0000",
     "start_time": "2020-11-10T02:50:39.024Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRun extends Thread{\n",
    "    Object obj;\n",
    "    public MyRun(String name,Object obj) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        super(name);\n",
    "        this.obj = obj;\n",
    "    }\n",
    "    public void run(){\n",
    "    //synchronized (obj) {\n",
    "            for (int i = 0; i < 10; i++) {\n",
    "                System.out.println(Thread.currentThread().getName()+ \" i=\"+i);\n",
    "                if(i%2 == 0)\n",
    "                    Thread.yield();\n",
    "            }\n",
    "    //}\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:51+0000",
     "start_time": "2020-11-10T02:51:16.670Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "//main\n",
    "Object obj = new Object();\n",
    "\n",
    "MyRun t1 = new MyRun(\"t1\",obj);\n",
    "MyRun t2 = new MyRun(\"t2\",obj);\n",
    "t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到他们两个基本上是交替运行，而不用yeild让步的话大概率一个线程执行完成了另一个线程才会执行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:53+0000",
     "start_time": "2020-11-10T02:53:46.492Z"
    }
   },
   "outputs": [],
   "source": [
    "class MyRun_ extends Thread{\n",
    "    Object obj;\n",
    "    public MyRun_(String name,Object obj) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        super(name);\n",
    "        this.obj = obj;\n",
    "    }\n",
    "    public void run(){\n",
    "    synchronized (obj) {\n",
    "            for (int i = 0; i < 10; i++) {\n",
    "                System.out.println(Thread.currentThread().getName()+ \" i=\"+i);\n",
    "                if(i%2 == 0)\n",
    "                    Thread.yield();\n",
    "            }\n",
    "    }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:54+0000",
     "start_time": "2020-11-10T02:54:12.765Z"
    }
   },
   "outputs": [],
   "source": [
    "//main\n",
    "Object obj = new Object();\n",
    "\n",
    "//MyRun_ t1 = new MyRun_(\"t1\",obj);\n",
    "MyRun_ t2 = new MyRun_(\"t2\",obj);\n",
    "//t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# priority\n",
    "priority代表线程的优先级，在JVM中优先级高的线程不一定会先运行，只是先运行的概率会比低优先级的线程大。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 中断\n",
    "对于一个正常运行的线程中，中断基本是没有作用的，只是作为一个标志位来查询。而线程的其他几种状态下如sleep、join、wait状态下是可以被中断，并且通过中断来跳出当前状态的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T02:55+0000",
     "start_time": "2020-11-10T02:55:57.950Z"
    }
   },
   "outputs": [],
   "source": [
    "class RunInt extends Thread{\n",
    "    public void run() {\n",
    "        while(!this.isInterrupted()){\n",
    "            synchronized (this) {\n",
    "                for (int i = 0; i < 10; i++) {\n",
    "                    System.out.println(Thread.currentThread().getName()+\" i=\"+i);\n",
    "                }\n",
    "                try {\n",
    "                    Thread.sleep(3000);\n",
    "                } catch (InterruptedException e) {\n",
    "                    System.out.println(Thread.currentThread().getName()+\" interrupted!\");\n",
    "                    break;\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "        System.out.println(Thread.currentThread().getName()+\" dead\");\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "start_time": "2020-11-10T02:56:17.975Z"
    }
   },
   "outputs": [],
   "source": [
    "//main\n",
    "RunInt r1 = new RunInt();\n",
    "r1.start();\n",
    "Thread.yield();\n",
    "synchronized (r1) {\n",
    "    System.out.println(Thread.currentThread().getName()+\" intertupt r1\");\n",
    "    r1.interrupt();\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，当主线程启动子线程后，子线程会进入到循环中并且进入到睡眠状态，然后主线程通过调用中断让子线程唤醒并且推出循环后死亡。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 死锁\n",
    "死锁指的是，两个线程互相等待对方释放资源导致卡死。例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:02+0000",
     "start_time": "2020-11-10T03:02:15.895Z"
    }
   },
   "outputs": [],
   "source": [
    "Thread t1 = new Thread(new Runnable() {\n",
    "    @Override\n",
    "    public void run() {\n",
    "        synchronized(\"A\") {\n",
    "            try {\n",
    "                Thread.sleep(1000);\n",
    "            } catch (InterruptedException e) {\n",
    "                e.printStackTrace();\n",
    "            }\n",
    "            synchronized(\"B\") {\n",
    "                System.out.println(\"haha\");\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "});\n",
    "\n",
    "Thread t2 = new Thread(new Runnable() {\n",
    "    @Override\n",
    "    public void run() {\n",
    "        synchronized(\"B\") {\n",
    "            synchronized(\"A\") {\n",
    "                System.out.println(\"xixi\");\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:02+0000",
     "start_time": "2020-11-10T03:02:21.150Z"
    }
   },
   "outputs": [],
   "source": [
    "t1.start();\n",
    "t2.start();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到t1线程获得A的锁然后睡眠，然后t2线程获得B的锁然后再等待A释放锁，而线程t1睡眠完成后在等待t2释放B的锁，导致程序卡死。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 生产者与消费者\n",
    "生产者和消费者是多线程中一个很常见的应用场景，这里首先用一个共享变量实现生产者和消费者，接着再使用阻塞队列实现。首先实现第一种：\n",
    "\n",
    "仓库代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:03+0000",
     "start_time": "2020-11-10T03:03:25.679Z"
    }
   },
   "outputs": [],
   "source": [
    "class Depot{\n",
    "    private int capacity;\n",
    "    private int size=0;\n",
    "    public Depot(int c) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        this.capacity = c;\n",
    "    }\n",
    "    public synchronized void product(int count) throws InterruptedException{\n",
    "        while(count>0){\n",
    "            if(size >= capacity)\n",
    "                wait();\n",
    "            //真实生产数量\n",
    "            int realcount = (capacity-size)>=count?count:(capacity-size);\n",
    "            System.out.print(Thread.currentThread().getName()+\"--本次想要生产：\"+count+\",本次实际生产:\"+realcount);\n",
    "            //下次生产数量\n",
    "            count = count - realcount;\n",
    "            //仓库剩余\n",
    "            size += realcount;\n",
    "            System.out.println(\",下次想要生产：\"+count+\",仓库真实容量：\"+size);\n",
    "            notifyAll();\n",
    "        }\n",
    "    }\n",
    "    public synchronized void comsume(int count) throws InterruptedException {\n",
    "        while(count>0){\n",
    "            if(size <= 0)\n",
    "                wait();\n",
    "            //真实消费数量\n",
    "            int realcount = (size>=count)?count:size;\n",
    "            System.out.print(Thread.currentThread().getName()+\"--本次想要消费:\"+count+\",本次真实消费：\"+realcount);\n",
    "            //下次消费数量\n",
    "            count = count - realcount;\n",
    "            //仓库剩余\n",
    "            size -= realcount;\n",
    "            System.out.println(\"下次想要消费：\"+count+\"，仓库剩余：\"+size);\n",
    "            notify();\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "生产者代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:03+0000",
     "start_time": "2020-11-10T03:03:44.814Z"
    }
   },
   "outputs": [],
   "source": [
    "class Producer {\n",
    "    Depot depot;\n",
    "    public Producer(Depot depot) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        this.depot = depot;\n",
    "    }\n",
    "    public void produce(final int count) {\n",
    "        new Thread(){\n",
    "            public void run() {\n",
    "                try {\n",
    "                    depot.product(count);\n",
    "                } catch (InterruptedException e) {\n",
    "                    // TODO Auto-generated catch block\n",
    "                    e.printStackTrace();\n",
    "                }\n",
    "            }\n",
    "        }.start();\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "消费者代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:04+0000",
     "start_time": "2020-11-10T03:04:07.872Z"
    }
   },
   "outputs": [],
   "source": [
    "class Consumer{\n",
    "    Depot depot;\n",
    "    public Consumer(Depot depot) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        this.depot = depot;\n",
    "    }\n",
    "    public void consume(final int count) {\n",
    "        new Thread(new Runnable() {\n",
    "\n",
    "            @Override\n",
    "            public void run() {\n",
    "                // TODO Auto-generated method stub\n",
    "                try {\n",
    "                    depot.comsume(count);\n",
    "                } catch (InterruptedException e) {\n",
    "                    // TODO Auto-generated catch block\n",
    "                    e.printStackTrace();\n",
    "                }\n",
    "            }\n",
    "        }).start();\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "main中代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:04+0000",
     "start_time": "2020-11-10T03:04:41.719Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thread-6--本次想要生产：60,本次实际生产:60,下次想要生产：0,仓库真实容量：60\n",
      "Thread-7--本次想要生产：50,本次实际生产:40,下次想要生产：10,仓库真实容量：100\n",
      "Thread-9--本次想要消费:50,本次真实消费：50下次想要消费：0，仓库剩余：50\n",
      "Thread-7--本次想要生产：10,本次实际生产:10,下次想要生产：0,仓库真实容量：60\n",
      "Thread-8--本次想要生产：30,本次实际生产:30,下次想要生产：0,仓库真实容量：90\n",
      "Thread-10--本次想要消费:110,本次真实消费：90下次想要消费：20，仓库剩余：0\n"
     ]
    }
   ],
   "source": [
    "Depot depot = new Depot(100);\n",
    "Producer producer = new Producer(depot);\n",
    "Consumer consumer = new Consumer(depot);\n",
    "producer.produce(60);\n",
    "producer.produce(50);\n",
    "producer.produce(30);\n",
    "consumer.consume(50);\n",
    "consumer.consume(110);\n",
    "producer.produce(40);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到实现了生产者消费者模型。\n",
    "\n",
    "第二种利用阻塞队列实现。直接利用阻塞队列当做仓库，生产者："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:06+0000",
     "start_time": "2020-11-10T03:06:18.670Z"
    }
   },
   "outputs": [],
   "source": [
    "class Pro1{\n",
    "    private BlockingQueue<Integer> blockingQueue1;\n",
    "    public Pro1(BlockingQueue<Integer> blockingQueue) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        this.blockingQueue1 = blockingQueue;\n",
    "    }\n",
    "    public void produce(final int count) {\n",
    "        new Thread(new Runnable() {\n",
    "\n",
    "            @Override\n",
    "            public void run() {\n",
    "                // TODO Auto-generated method stub\n",
    "                for (int i = 0; i < count; i++) {\n",
    "                    try {\n",
    "                        Thread.sleep(100);\n",
    "                        blockingQueue1.put(100);\n",
    "                        System.out.println(\"生产者，仓库剩余容量\"+blockingQueue1.size());\n",
    "                    } catch (InterruptedException e) {\n",
    "                        // TODO Auto-generated catch block\n",
    "                        e.printStackTrace();\n",
    "                    }\n",
    "                }\n",
    "            }\n",
    "        }).start();\n",
    "\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "消费者："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:06+0000",
     "start_time": "2020-11-10T03:06:22.422Z"
    }
   },
   "outputs": [],
   "source": [
    "class Con1{\n",
    "    private BlockingQueue<Integer> blockingQueue;\n",
    "    public Con1(BlockingQueue<Integer> blockingQueue) {\n",
    "        // TODO Auto-generated constructor stub\n",
    "        this.blockingQueue = blockingQueue;\n",
    "    }\n",
    "    public void consume(final int count) {\n",
    "        new Thread(new Runnable() {\n",
    "\n",
    "            @Override\n",
    "            public void run() {\n",
    "                // TODO Auto-generated method stub\n",
    "                for (int i = 0; i < count; i++) {\n",
    "                    try {\n",
    "                        Thread.sleep(100);\n",
    "                        blockingQueue.take();\n",
    "                        System.out.println(\"消费者，本次仓库剩余：\"+blockingQueue.size());\n",
    "                    } catch (InterruptedException e) {\n",
    "                        // TODO Auto-generated catch block\n",
    "                        e.printStackTrace();\n",
    "                    }\n",
    "                }\n",
    "            }\n",
    "        }).start();\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "main函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-10T03:06+0000",
     "start_time": "2020-11-10T03:06:24.566Z"
    }
   },
   "outputs": [],
   "source": [
    "BlockingQueue<Integer> blockingQueue = new ArrayBlockingQueue<Integer>(5);\n",
    "Pro1 pro1 = new Pro1(blockingQueue);\n",
    "Con1 con1 = new Con1(blockingQueue);\n",
    "pro1.produce(10);\n",
    "con1.consume(7);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里阻塞队列的作用是，当容量不足的消费者进入等待队列，而当容量有剩余的时候消费者被唤醒，当容量已满的时候生产者进入等待队列，当容量被消费后生产者被唤醒。"
   ]
  }
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